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Record W4214930295 · doi:10.1108/jitlp-09-2021-0051

Intellectual property and the African continental free trade area: lessons and recommendations for the IP protocol

2022· article· en· W4214930295 on OpenAlexfundno aff
Caroline B. Ncube

Bibliographic record

VenueJournal of International Trade Law and Policy · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsnot available
FundersFondations communautaires du CanadaInternational Development Research Centre
KeywordsIntellectual propertyNegotiationProtocol (science)OriginalityArchitectureValue (mathematics)Meaning (existential)Computer scienceEconomicsBusinessLaw and economicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Purpose This paper aims to explore the contours of the future intellectual property (IP) protocol of the African Continental Free Trade Area (AfCFTA) Agreement. Design/methodology/approach This paper frames the IP protocol within the architecture of the AfCFTA Agreement, meaning that it will follow the structure of other protocols and will be guided by the Agreement’s foundational principles and objectives. With the place, shape and form of the protocol so established, the paper considers the substantive aspects that ought to be addressed. It also considers provisions on technical assistance, capacity building and cooperation. Findings The paper finds that the Tripartite Free Trade Phase 2 IP agenda is a credible starting place, which must be broadened to better meet gendered challenges and the continent’s developmental priorities. This will entail including provisions on specific aspects enumerated in the paper, which must be aligned with provisions on technical assistance, capacity building and cooperation to enhance implementation. The best outcomes in the negotiation, adoption and implementation of the IP protocol will be achieved by an inclusive approach incorporating all national, sub-regional and regional institutions guided by coherent policy and coordinated to ensure efficiency in resources and capacity mobilisation. Originality/value To the best of the author’s knowledge, this is the first paper to formally consider both the architecture and substantive provisions of the future AfCFTA IP protocol with specific focus on gendered dimensions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.117
GPT teacher head0.296
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2022
Admission routes1
Has abstractyes

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